code: def _get_encoder_config(
      cls,
      observation_space: gym.Space,
      **kwargs,
  ):
      if (
          isinstance(observation_space, gym.spaces.Box)
          and observation_space.shape == MOBILENET_INPUT_SHAPE
      ):
          # Inject our custom encoder here, only if the observation space fits it
          return MobileNetV2EncoderConfig()
      else:
          return super()._get_encoder_config(
              observation_space, **kwargs
          )
  
file_path: ray/python/ray/rllib/examples/catalog/mobilenet_v2_encoder.py
imports: import gymnasium
  import numpy
  from ray.rllib.algorithms.ppo.ppo import PPOConfig
  from ray.rllib.algorithms.ppo.ppo_catalog import PPOCatalog
  from ray.rllib.examples.models.mobilenet_v2_encoder import MobileNetV2EncoderConfig, MOBILENET_INPUT_SHAPE
  from ray.rllib.core.rl_module.rl_module import SingleAgentRLModuleSpec
  from ray.rllib.examples.env.random_env import RandomEnv
label_desc: Use image node_id 1 for calling the MobileNetEnhancedPPOCatalog obj's underlying member method code with example usage: obj._get_encoder_config(cls, observation_space) and returns: MobileNetV2EncoderConfig, super